Applying Neural Network Approach with Imperialist Competitive Algorithm for Software Reliability Prediction

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Shirin Noekhah Naomie binti Salim Nor Hawaniah Zakaria


Software systems exist in different critical domains. Software reliability assessment has become a critical issue due to the variety levels of software complexity. Software reliability, as a sub-branch of software quality, has been exploited to evaluate to what extend the desired software is trustable. To overcome the problem of dependency to human power and time limitation for software reliability prediction, researchers consider soft computing approaches such as Neural Network and Fuzzy Logic. These techniques suffer from some limitations including lack of analyzing mathematical foundations, local minima trapping and convergence problem. This study develops a novel model for software reliability prediction through the combination of Multi-Layer Perceptron Neural Network (MLP) and Imperialist Competitive Algorithm (ICA). The proposed model has solved some of the problems of existing methods such as convergence problem and demanding on huge number of data. This model can be used in complicated software systems. The results prove that both training and testing phases of this model outperform existing approaches in terms of predicting the number of software failures.


Soft computing, reliability of software, Multi-Layer Perceptron Neural Network, Imperialist Competitive Algorithm


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[2] N. Karunanithi, D. Whitley and YK. Malaiya, Prediction of software reliability using connectionist models, IEEE Transactions on Software Engineering, 1992.
[3] WA. Adnan and MH. Yaacob, An integrated neural-fuzzy system of software reliability prediction, In Software Testing, Reliability and Quality Assurance, Conference Proceedings., First International Conference, pp. 154-158, 1994.
[4] JY. Park, SU. Lee and JH. Park, Neural network modeling for software reliability prediction from failure time data, Journal of Electrical Engineering and Information Science. 1999.
[5] N. Karunanithi, D. Whitley, YK. Malaiya, Using neural networks in reliability prediction, IEEE Software, 1992.
[6] KY. Cai, L. Cai, WD. Wang, ZY. Yu and D. Zhang, On the neural network approach in software reliability modeling, Journal of Systems and Software, 2001.
[7] L. Tian and A. Noore, On-line prediction of software reliability using an evolutionary connectionist model, Journal of Systems and Software, 2005.
[8] L. Tian and A. Noore, Evolutionary neural network modeling for software cumulative failure time prediction, Reliability Engineering & system safety, 2005.
[9] Z. Jun, Prediction of software reliability using connectionist models. Expert Systems with Applications, 2009.
[10] C. Jin, Software reliability prediction based on support vector regression using a hybrid genetic algorithm and simulated annealing algorithm, IET software, 2011.
[11] C. Jin and SW. Jin, Software reliability prediction model based on support vector regression with improved estimation of distribution algorithms, Applied Soft Computing, 2014.
[12] J. Park and J. Baik. Improving software reliability prediction through multi-criteria based dynamic model selection and combination, Journal of Systems and Software, 2015.
[13] Y. Wu and R. Yang. Study of software reliability prediction based on GR neural network, In Reliability, Maintainability and Safety (ICRMS), 9th International Conference, pp. 688-693, 2011.
[14] MC. Liu, W. Kuo and T. Sastri, An exploratory study of a neural network approach for reliability data analysis, Quality and Reliability Engineering International, 1995.
[15] PT. Chang, KP. Lin and PF. Pai, Hybrid learning fuzzy neural models in forecasting engine system reliability, In Proceeding of the fifth Asia Pacific industrial engineering and management systems conference, pp. 2361-2366, 2004.
[16] VN. Vapnik and V. Vapnik, Statistical learning theory, New York: Wiley, 1998.
[17] MK. Bhuyan, DP. Mohapatra and S. Sethi, Prediction strategy for software reliability based on recurrent neural network. In Computational Intelligence in Data Mining, pp. 295-303, 2016.
[18] PR. Bal, N. Jena and DP. Mohapatra, Software reliability prediction based on ensemble models, In Proceeding of International Conference on Intelligent Communication, Control and Devices, pp. 895-902, 2017.
[19] S. Noekhah, AA. Hozhabri and HS. Rizi, Software reliability prediction model based on ICA algorithm and MLP neural network, In e-Commerce in Developing Countries: With Focus on e-Security (ECDC), 7th International Conference, pp. 1-15, 2013.